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서울대학교 언론정보학과 BK21 FOUR "자유롭고 책임있는 AI 미디어" 교육연구단·언론정보연구소 <제5회 Emerging Scholars Series> 개최 안내

1. 회원님들의 건승을 기원합니다.

2. 서울대학교 언론정보학과 BK21 FOUR "자유롭고 책임있는 AI 미디어" 교육연구단과 언론정보연구소에서 <제5회 Emerging Scholars Series>를 다음과 같이 개최합니다. 회원님들의 많은 관심과 참여 바랍니다.
 

- 다 음 -


□ 일시: 2024년 3월 8일(금) 12:30~14:00

□ 참여 링크: https://snu-ac-kr.zoom.us/j/92903019743
※ 특강 참여 시 화면은 켜주시기 바랍니다.

□ 발표자: Sang Jung Kim (University of Iowa)
  Sang Jung Kim is an Assistant Professor of Journalism and Mass Communication at the University of Iowa. She earned her doctoral degree in Journalism and Mass Communication at the University of Wisconsin-Madison. Her research focuses on the interaction between technology, politics, and social identity, with particular attention to the mediating role of social media platforms and the spread of multi-modal information to the public. Her research has been published in the Journal of Communication, New Media and Society, Communication Methods & Measures, Political Communication, International Journal of Press/Politics, Information, Communication, and Society, Journal of Computer-Mediated Communication, and Computational Communication Research, among other peer-reviewed journals.

□ 제목: Navigating framing effects in the digital age: Understanding the role of emotions and multi-modality in persuasive messages on social media.

□ 초록
Communication processes have become dynamic in the digital era. The public is increasingly accustomed to exchanging emotional expressions on social media platforms, facilitating different message modalities, such as texts, images, or videos, through which strategic communicators build relationships with the public. Could we understand how strategic actors utilize emotions and various message modalities to persuade audiences in this digital era? Drawing from the emotions-as-frames model and affective intelligence theory, this research talk presents two studies using computational approaches examining how conspiracy actors use emotional and multi-modal dynamics on social media platforms. The first study, which applies supervised machine learning and computational linguistics, shows how emotional appeals are used in conspiracy and debunking videos on YouTube to draw engagement. The second study employs deep learning-based computer vision techniques and computational linguistics to analyze how anti-vaxxers utilize emotional frames in various message modalities on TikTok. Both studies advance our understanding of how persuasion occurs in digital media and how computational approaches can illuminate the underlying process.

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